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- https://math.libretexts.org/Courses/De_Anza_College/Linear_Algebra%3A_A_First_Course/02%3A_Matrices/2.02%3A_The_Inverse_of_a_MatrixThis page explores matrix operations, focusing on the identity matrix and matrix inverses, including their existence, uniqueness, and the method for finding inverses through augmented matrices and row...This page explores matrix operations, focusing on the identity matrix and matrix inverses, including their existence, uniqueness, and the method for finding inverses through augmented matrices and row operations. It provides examples illustrating both the derivation of inverses and scenarios where matrices lack inverses.
- https://math.libretexts.org/Bookshelves/Linear_Algebra/Interactive_Linear_Algebra_(Margalit_and_Rabinoff)/04%3A_DeterminantsThis page discusses matrix equations, focusing on solving Ax=b, determining eigenvalues and eigenvectors, and finding approximate solutions. The current chapter emphasizes determinants, covering t...This page discusses matrix equations, focusing on solving Ax=b, determining eigenvalues and eigenvectors, and finding approximate solutions. The current chapter emphasizes determinants, covering their definition, properties, and computation methods. It includes cofactor expansions as a recursive calculation method and explores the geometric interpretation of determinants in relation to volumes in multivariable calculus.
- https://math.libretexts.org/Bookshelves/Linear_Algebra/Interactive_Linear_Algebra_(Margalit_and_Rabinoff)/06%3A_Orthogonality/6.04%3A_The_Method_of_Least_SquaresThis page covers orthogonal projections in vector spaces, detailing the advantages of orthogonal sets and defining the simpler Projection Formula applicable with orthogonal bases. It includes examples...This page covers orthogonal projections in vector spaces, detailing the advantages of orthogonal sets and defining the simpler Projection Formula applicable with orthogonal bases. It includes examples of projecting vectors onto subspaces, emphasizes the importance of orthogonal bases, and introduces the Gram-Schmidt process for generating orthogonal bases from sets of vectors.
